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Paper Citation Record · LEDGER

Boosting the Rating Prediction with Click Data and Textual Contents

As of 23 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:1908.07749.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1908.07749 v2

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:12:43.838404Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a9050f10-a01a-4cc6-ab02-5ba997d4c011 · outbound

This paper cites Sarwar, George Karypis, Joseph A.

Boosting the Rating Prediction with Click Data and Textual Contents Sarwar, George Karypis, Joseph A

Reference 1

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Source-reported events for the cited work

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Observation b0b6e37e-f338-40b6-a519-c50d9727287d · outbound

This paper cites A comprehensive survey of neighborhood-based recommendation methods.

Boosting the Rating Prediction with Click Data and Textual Contents A comprehensive survey of neighborhood-based recommendation methods

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation d6c33104-2a01-46f0-be9c-0da6452c83d9 · outbound

This paper cites an unresolved cited work.

Boosting the Rating Prediction with Click Data and Textual Contents Unresolved cited work

Reference 3

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Source-reported events for the cited work

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Observation cae9797d-ecd2-45ba-aecc-7fdff333df32 · outbound

This paper cites Probabilistic matrix factorization.

Boosting the Rating Prediction with Click Data and Textual Contents Probabilistic matrix factorization

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 60b1f341-7939-40dc-91ba-508837379a0c · outbound

This paper cites Collaborative filtering with temporal dynamics.

Boosting the Rating Prediction with Click Data and Textual Contents Collaborative filtering with temporal dynamics

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 5fb0c4f8-53ca-4533-82cd-1d3b7b68f086 · outbound

This paper cites an unresolved cited work.

Boosting the Rating Prediction with Click Data and Textual Contents Unresolved cited work

Reference 6

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Source-reported events for the cited work

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Observation 54fd2ce2-bb9d-4f65-8c18-aa04f29db5f1 · outbound

This paper cites Collaborative deep learning for recommender systems.

Boosting the Rating Prediction with Click Data and Textual Contents Collaborative deep learning for recommender systems

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation eaa7ab9d-05f2-44f8-8041-899e7b67a709 · outbound

This paper cites an unresolved cited work.

Boosting the Rating Prediction with Click Data and Textual Contents Unresolved cited work

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation ca68300f-98b3-41d0-bec3-a68cc958a91d · outbound

This paper cites Collaborative variational autoencoder for recommender systems.

Boosting the Rating Prediction with Click Data and Textual Contents Collaborative variational autoencoder for recommender systems

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation b3b18630-54a6-4fc8-8603-4a1d6c529e4c · outbound

This paper cites Corrado, and Jeffrey Dean.

Boosting the Rating Prediction with Click Data and Textual Contents Corrado, and Jeffrey Dean

Reference 10

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Source-reported events for the cited work

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Observation f582652c-8cd9-442e-91e8-08258c2784ce · outbound

This paper cites Glove: Global vectors for word representation.

Boosting the Rating Prediction with Click Data and Textual Contents Glove: Global vectors for word representation

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 56a92b72-64ac-474b-9450-46305b8ba732 · outbound

This paper cites A probabilistic model for the cold-start problem in rating prediction using click data.

Boosting the Rating Prediction with Click Data and Textual Contents A probabilistic model for the cold-start problem in rating prediction using click data

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation bbb1a108-d654-4c89-af32-1b0c7038a054 · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

Boosting the Rating Prediction with Click Data and Textual Contents Efficient Estimation of Word Representations in Vector Space

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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This paper cites Distributed representations of sentences and documents.

Boosting the Rating Prediction with Click Data and Textual Contents Distributed representations of sentences and documents

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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This paper cites A generative word embedding model and its low rank positive semidefinite solution.

Boosting the Rating Prediction with Click Data and Textual Contents A generative word embedding model and its low rank positive semidefinite solution

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation d5f80888-4afe-473f-ab14-4dbb917b8452 · outbound

This paper cites Neural word embedding as implicit matrix factorization.

Boosting the Rating Prediction with Click Data and Textual Contents Neural word embedding as implicit matrix factorization

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 950d327e-e6c1-43ba-8fcf-a0184422b396 · outbound

This paper cites an unresolved cited work.

Boosting the Rating Prediction with Click Data and Textual Contents Unresolved cited work

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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This paper cites Extracting semantic representations from word co-occurrence statistics: A computa- tional study.

Boosting the Rating Prediction with Click Data and Textual Contents Extracting semantic representations from word co-occurrence statistics: A computa- tional study

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Boosting the Rating Prediction with Click Data and Textual Contents Unresolved cited work

Reference 19

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Source-reported events for the cited work

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Observation e7f0b449-679f-4ef5-9026-d80eb063c8d3 · outbound

This paper cites Bell and Yehuda Koren.

Boosting the Rating Prediction with Click Data and Textual Contents Bell and Yehuda Koren

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation d2364dbc-7f92-4882-ba20-efb85c6efcd0 · outbound

This paper cites Npe: Neural personalized embedding for collaborative filtering.

Boosting the Rating Prediction with Click Data and Textual Contents Npe: Neural personalized embedding for collaborative filtering

Reference 21

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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This paper cites City recommender system based on a latent topic model.

Boosting the Rating Prediction with Click Data and Textual Contents City recommender system based on a latent topic model

Reference 22

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation f03957be-3eb0-4ca2-b0ab-d731dca177e0 · outbound

This paper cites Collaborative item embedding model for implicit feedback data.

Boosting the Rating Prediction with Click Data and Textual Contents Collaborative item embedding model for implicit feedback data

Reference 23

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 801d6d36-2f03-425f-afb2-eebda2c97812 · outbound

This paper cites A hierarchical bayesian factorization model for implicit and explicit feedback data.

Boosting the Rating Prediction with Click Data and Textual Contents A hierarchical bayesian factorization model for implicit and explicit feedback data

Reference 24

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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This paper cites Kanjirathinkal, and Mohan Kankanhalli.

Boosting the Rating Prediction with Click Data and Textual Contents Kanjirathinkal, and Mohan Kankanhalli

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 7c01a466-e604-4a7e-9e7a-46a10d3a0a9f · outbound

This paper cites Learning representations from product titles for modeling shopping transac- tions.

Boosting the Rating Prediction with Click Data and Textual Contents Learning representations from product titles for modeling shopping transac- tions

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation e61aad60-b8f6-49fd-bf8d-7f420e20b4b1 · outbound

This paper cites Vbpr: Visual bayesian personalized ranking from implicit feedback.

Boosting the Rating Prediction with Click Data and Textual Contents Vbpr: Visual bayesian personalized ranking from implicit feedback

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:12:44.000747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 2cbeaab3-0712-4a9d-bd37-147455f97c6b · outbound

This paper cites Unifying explicit and implicit feedback for collaborative filtering.

Boosting the Rating Prediction with Click Data and Textual Contents Unifying explicit and implicit feedback for collaborative filtering

Reference 28

Resolution
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raw_fallback, observed 2026-08-14T12:12:43.977253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 4e8381ef-5168-4ebe-b895-221262a0b040 · outbound

This paper cites Expectation-maximization collaborative filtering with explicit and implicit feedback.

Boosting the Rating Prediction with Click Data and Textual Contents Expectation-maximization collaborative filtering with explicit and implicit feedback

Reference 29

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation d072e4b7-3c99-4ed6-9dfe-aee3e27d7407 · outbound

This paper cites Transfer to rank for heterogeneous one-class collaborative filtering.

Boosting the Rating Prediction with Click Data and Textual Contents Transfer to rank for heterogeneous one-class collaborative filtering

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:12:43.939626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation b43945b5-714d-4b52-bd2e-a957bdaa4dfb · outbound

This paper cites Item2vec: Neural item embedding for collaborative filtering.

Boosting the Rating Prediction with Click Data and Textual Contents Item2vec: Neural item embedding for collaborative filtering

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:12:43.920223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 9e0f3af4-4757-4203-b1fe-4b8146c7f6ca · outbound

This paper cites an unresolved cited work.

Boosting the Rating Prediction with Click Data and Textual Contents Unresolved cited work

Reference 32

Resolution
unresolved
raw_fallback, observed 2026-08-14T12:12:43.901090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Pith citing papers

No inbound Pith citation observations are available.